\begin{table}[H]
\small
\centering
\caption{Male migration increases female autonomy}
\begin{tabular}{lcccccccccc}
\toprule
&  \multicolumn{1}{c}{\textbf{Political Engagement}} & \multicolumn{1}{c}{\textbf{Bargaining Power}}& \multicolumn{1}{c}{\textbf{Mobility}} &\multicolumn{1}{c}{\textbf{Access to Cash}}\\
&(1)&(2) & (3) & (4) \\
\hline
\hline

Wave 2              &        0.21***&       0.068***&        0.11***&        0.13***\\
                    &     (0.017)   &     (0.011)   &    (0.0097)   &     (0.011)   \\
Migrant Husband  $\times$ Wave 2&       0.080** &       0.036*  &        0.18***&       0.012   \\
                    &     (0.032)   &     (0.019)   &     (0.020)   &     (0.020)   \\
\midrule
Individual FE & Yes & Yes & Yes & Yes\\
 \midrule
Adj.R2              &      0.2669   &      0.0933   &      0.1719   &      0.0722   \\
Observations        &        1750   &        7120   &        8124   &        8092   \\
\bottomrule
\end{tabular}
\label{tab:matching}
\begin{tablenotes}
\noindent Notes: Estimates from a difference-in-difference specification using a matched sample. Matching is done on individual and village level covariates before migration i.e. in Wave 1 (\autoref{fig:psm_matching}). Each woman with a migrant husband is wave two is matched with five women with co-resident husbands. Since the sample here is limited to rural areas, I lose 1/3 of the treated units. I only consider cases where women can answer all questions within an index. During the analysis STATA dropped all singleton variables. All errors are clustered at the village level – primary sampling unit. Source: IHDS I and II.
\end{tablenotes}
\end{table}
